{"id":"W6947706383","doi":"10.3886/e194845","title":"Data and Code for: Careers and Intergenerational Income Mobility","year":2024,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Université du Québec à Montréal","funders":"","keywords":"Microdata (statistics); Census; Persistence (discontinuity); Survey of Income and Program Participation; Socioeconomic status; Social mobility; Occupational mobility","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006027937,0.0002459104,0.0002577694,0.00005314222,0.00008241113,0.0001345042,0.001343822,0.0004451353,0.0000140648],"category_scores_gemma":[0.0007880726,0.0002142277,0.00002510819,0.00004781915,0.0004009524,0.00001063081,0.004772326,0.0002225171,0.000009039885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009662116,"about_ca_system_score_gemma":0.0001040157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005052013,"about_ca_topic_score_gemma":0.001111466,"domain_scores_codex":[0.9981191,0.00002894535,0.0002624595,0.001228668,0.0001452107,0.0002156305],"domain_scores_gemma":[0.9974717,0.00006234434,0.00008036112,0.002237059,0.00003777309,0.0001107508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000298056,0.00001761453,0.00008612858,0.0003045515,0.0001130455,0.000003967088,0.000004766478,9.280748e-8,0.0005989845,0.000004403688,0.9953483,0.003488366],"study_design_scores_gemma":[0.000219935,0.0001270866,0.00006932469,0.00007027911,0.0001254139,0.00003144719,0.00003422541,0.0002819026,0.0001111318,0.00006660237,0.9986162,0.0002464225],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003973568,0.008867945,0.0002016227,0.0003585471,0.0004842497,0.0001766246,0.9859162,0.00001780571,0.000003444711],"genre_scores_gemma":[0.0006600337,0.00343041,0.001953786,0.0002449406,0.0005203051,0.00002444051,0.993086,0.00001830901,0.00006172962],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007169853,"threshold_uncertainty_score":0.8735953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06372702490498836,"score_gpt":0.3516261895954946,"score_spread":0.2878991646905062,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}